pseudo relevance feedback
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2022 ◽  
Vol 12 (1) ◽  
pp. 0-0

In this paper, the authors propose and readapt a new concept-based approach of query expansion in the context of Arabic information retrieval. The purpose is to represent the query by a set of weighted concepts in order to identify better the user's information need. Firstly, concepts are extracted from the initially retrieved documents by the Pseudo-Relevance Feedback method, and then they are integrated into a semantic weighted tree in order to detect more information contained in the related concepts connected by semantic relations to the primary concepts. The authors use the “Arabic WordNet” as a resource to extract, disambiguate concepts and build the semantic tree. Experimental results demonstrate that measure of MAP (Mean Average Precision) is about 10% of improvement using the open source Lucene as IR System on a collection formed from the Arabic BBC news.


2022 ◽  
Vol 59 (1) ◽  
pp. 102734
Author(s):  
Min Pan ◽  
Junmei Wang ◽  
Jimmy X. Huang ◽  
Angela J. Huang ◽  
Qi Chen ◽  
...  

2021 ◽  
Author(s):  
Xiao Wang ◽  
Craig Macdonald ◽  
Nicola Tonellotto ◽  
Iadh Ounis

Author(s):  
Avi Arampatzis ◽  
Georgios Peikos ◽  
Symeon Symeonidis

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